Consumers have long needed an efficient way to discover and evaluate information about content goods, services, and other objects. The typical person finds information about content and objects by word of mouth, by checking the classified advertisements section of the newspaper, or perhaps by submitting a text query to an internet search engine, such as Google. None of those methods are completely satisfactory solutions to the problem of finding content and objects based upon their characteristics as well as their location. Problems associated with current mapping technology further limit effective search for objects and content. For example, current mapping technology is focused upon displaying a single result such as a restaurant or destination and not on search or discovery. Traditional non-interactive maps are based on the display of a static image for a map. This requires the computer hosting the map to redraw an image that includes both vector and raster data whenever a user pans across or zooms within the map. In this way, non-interactive maps severely limit the speed and quality of the user experience. This problem is further exacerbated if a search is refined based on narrowing the range of characteristics associated with an object or content, causing further performance limitations in the user experience as additional lag is caused by the server refreshing the content again. It is difficult to manipulate objects and content in a non-interactive map without requiring the computer hosting the map to redraw the map image. Targeted advertising with traditional non-interactive maps is limited and cannot display content and advertising related to the user's map usage in real time. For example, seamlessly changing advertisements as the user traverses from one geographic region to another, or zooms from the low level to a high level is not possible with non-interactive maps due to the time required to generate static map images. To maximize the value of additional content and advertising to both map users and advertisers, the content and advertising must be made as relevant as possible to the user. The current noninteractive mapping systems have severe limitations associated with determining and maximizing the relevance of objects and content and advertising that are displayed in the context of user searches, and search result interactions. Moreover, current non-interactive maps do not allow the sale of advertisements associated with objects and content based on interactive mapping movement, a selected bounding region on the map, a group of regions, zoom level or elevation, characteristics of objects and content, or grouped search results. Further, current non-interactive maps do not allow for dynamic pricing models for advertising, the ability to estimate ad costs, or the ability to define an ad location bounding box in three dimensions using X, Y, and Z coordinates. Unique aspects of the U.S. residential real estate market present a set of problems that make search, interactive mapping, and advertising systems particularly useful. There is a need for a system that overcomes limitations of current search, non-interactive mapping, and local advertising as well as providing additional benefits.